The present invention relates to apparatus and methods for classifying a signal source, namely, a moving vehicle, both as a moving vehicle and as a class of moving vehicle from estimates of its length, weight, speed, direction, etc. This involves signal processing and, more particularly, involves deconvolving received data into an underlying source signal. It further involves estimating the impulse signal model for the common source of one or more received signals.
There are many advanced signal processing applications in which one wishes to estimate the characteristics of a signal source from received signals. Given sufficient information, time, and processing power, a signal can be deconvolved into its source signal through compensation for various influences such as the propagation path. Alternatively, for known source signals the characteristics of the signal path can be derived. This latter technique is used extensively in geological subsurface mapping.
While the art has developed extensive tools for signal source and path analysis, these tools generally are very complex and difficult to apply. The computational schemes employed are computationally intensive and highly complex, often requiring large computer systems operating over many hours or days to derive a useful estimate. The complexity of the approaches taught or known in the art can be seen in reference works in the area such as: "Maximum Likelihood Deconvolution", by J. M. Mendel, Springer-Verlag, N.Y. Inc. 1990; "Signal Processing: The Model-Based Approach" by James V. Candy, McGraw-Hill 1986; or "Lessons in Estimation Theory" by J. M. Mendel, Prentice Hall, Inc. 1987.
For power-limited portable or mobile applications such complexity is unsatisfactory. At the same time, in many applications only a small amount of information for signal and path parameters is known, making application of the more complex and complete approaches impractical. Many signal detection and analysis applications also require that the analysis time be short, with real-time estimation being preferred. The art has not provided a technique meeting these constraints which also provides a highly accurate estimate.
What is needed then is a low power, high speed technique for classifying a moving vehicle by deconvolving received data signals, the technique also being able to account for the intervening signal path dynamics. It would be advantageous if the technique could be achieved with minimum complexity and cost.